Statistical Methods for Survival Data Analysis
(Sprache: Englisch)
This leading reference, now in its third edition, deals with the statistical methods for analyzing survival data derived from laboratory studies of animals, clinical and epidemiological studies of humans, and other appropriate applications. Special...
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Produktinformationen zu „Statistical Methods for Survival Data Analysis “
This leading reference, now in its third edition, deals with the statistical methods for analyzing survival data derived from laboratory studies of animals, clinical and epidemiological studies of humans, and other appropriate applications. Special consideration is given to the study of survival data in biomedical sciences, though all the methods are suitable for applications in industrial reliability, social sciences, and business.
Klappentext zu „Statistical Methods for Survival Data Analysis “
Third Edition brings the text up to date with new material and updated references. New content includes an introduction to left and interval censored data; the log-logistic distribution; estimation procedures for left and interval censored data; parametric methods iwth covariates; Cox's proportional hazards model (including stratification and time-dependent covariates); and multiple responses to the logistic regression model. Coverage of graphical methods has been deleted. Large data sets are provided on an FTP site for readers' convenience. Bibliographic remarks conclude each chapter.
Inhaltsverzeichnis zu „Statistical Methods for Survival Data Analysis “
Preface.Introduction.
Functions of Survival Time.
Examples of Survival Data Analysis.
Nonparametric Methods of Estimating Survival Functions.
Nonparametric Methods for Comparing Survival Distributions.
Some Well-Known Parametric Survival Distributions and Their Applications.
Estimation Procedures for Parametric Survival Distributions Without Covariates.
Graphical Methods in Survival Distribution Fitting.
Tests of Goodness of Fit and Distribution Selection.
Parametric Methods for Comparing Two Survival Distributions.
Parametric Methods for Regression Model Fitting and Identification of Prognostic Factors.
Identification of Prognostic Factors Related to Survival Time: Cox Proportional Hazards Model.
Identification of Prognostic Factors Related to Survival Time: Nonproportional Hazards Models.
Identification of Risk Factors Related to Dichotomous and Polychotomous Outcomes.
Appendix A: Newton-Raphson Method.
Appendix B: Statistical Tables.
References.
Index.
Autoren-Porträt von Elisa T. Lee, John Wenyu Wang
John Wenyu Wang, PhD, is an Associate Professor of Biostatistics at the University of Oklahoma Health Sciences Center. He received a master's degree from the Academy of Sciences of China and his doctorate from the University of Maryland. Elisa T. Lee, PhD, is George Lynn Cross Research Professor of Biostatistics and Epidemiology and Director of the Center for American Indian Health Research at the University of Oklahoma Health Sciences Center. She received a master's degree from the University of California at Berkeley and her doctorate from New York University. The author of the previous editions of Statistical Methods for Survival Data Analysis, Professor Lee is a Fellow of the American Statistical Association and member of the Society for Epidemiological Research and the American Diabetes Association.
Bibliographische Angaben
- Autoren: Elisa T. Lee , John Wenyu Wang
- 2003, 3rd ed., 558 Seiten, Gebunden, Englisch
- Verlag: Wiley & Sons
- ISBN-10: 0471369977
- ISBN-13: 9780471369974
Sprache:
Englisch
Rezension zu „Statistical Methods for Survival Data Analysis “
"This third edition is a significant upgrade...this remains an excellent choice or a basic textbook in survival analysis..." (Technometrics, Vol. 45, No. 4, November 2003)
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